Humans as Animal Sentinels for Forecasting Asthma Events: Helping Health Services Become More Responsive

The concept of forecasting asthma using humans as animal sentinels is uncommon. This study explores the plausibility of predicting future asthma daily admissions using retrospective data in London (2005-2006). Negative binomial regressions were used in modeling; allowing the non-contiguous autoregressive components. Selected lags were based on partial autocorrelation function (PACF) plot with a maximum lag of 7 days. The model was contrasted with naïve historical and seasonal models. All models were cross validated. Mean daily asthma admission in 2005 was 27.9 and in 2006 it was 28.9. The lags 1, 2, 3, 6 and 7 were independently associated with daily asthma admissions based on their PACF plots. The lag model prediction of peak admissions were often slightly out of synchronization with the actual data, but the days of greater admissions were better matched than the days of lower admissions. A further investigation across various populations is necessary. © 2012 Soyiri, Reidpath

Evolving forecasting classifications and applications in health forecasting

Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths.Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/ temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1).The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2)This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept. © 2013 Soyiri, Reidpath

Semistructured black-box prediction: proposed approach for asthma admissions in London

Asthma is a global public health problem and the most common chronic disease among children. The factors associated with the condition are diverse, and environmental factors appear to be the leading cause of asthma exacerbation and its worsening disease burden. However, it remains unknown how changes in the environment affect asthma over time, and how temporal or environmental factors predict asthma events. The methodologies for forecasting asthma and other similar chronic conditions are not comprehensively documented anywhere to account for semistructured noncausal forecasting approaches. This paper highlights and discusses practical issues associated with asthma and the environment, and suggests possible approaches for developing decision-making tools in the form of semistructured black-box models, which is relatively new for asthma. Two statistical methods which can potentially be used in predictive modeling and health forecasting for both anticipated and peak events are suggested. Importantly, this paper attempts to bridge the areas of epidemiology, environmental medicine and exposure risks, and health services provision. The ideas discussed herein will support the development and implementation of early warning systems for chronic respiratory conditions in large populations, and ultimately lead to better decision-making tools for improving health service delivery. © 2012 Soyiri and Reidpath, publisher and licensee Dove Medical Press Ltd

Asthma Length of Stay in Hospitals in London 2001–2006: Demographic, Diagnostic and Temporal Factors

Asthma is a condition of significant public health concern associated with morbidity, mortality and healthcare utilisation. This study identifies key determinants of length of stay (LOS) associated with asthma-related hospital admissions in London, and further explores their effects on individuals. Subjects were primarily diagnosed and admitted for asthma in London between 1st January 2001 and 31st December 2006. All repeated admissions were treated uniquely as independent cases. Negative binomial regression was used to model the effect(s) of demographic, temporal and diagnostic factors on the LOS, taking into account the cluster effect of each patient's hospital attendance in London. The median and mean asthma LOS over the period of study were 2 and 3 days respectively. Admissions increased over the years from 8,308 (2001) to 10,554 (2006), but LOS consistently declined within the same period. Younger individuals were more likely to be admitted than the elderly, but the latter significantly had higher LOS (p<0.001). Respiratory related secondary diagnoses, age, and gender of the patient as well as day of the week and year of admission were important predictors of LOS. Asthma LOS can be predicted by socio-demographic factors, temporal and clinical factors using count models on hospital admission data. The procedure can be a useful tool for planning and resource allocation in health service provision

Complementary feeding and the early origins of obesity risk: a study protocol

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-0420Introduction The rise in the prevalence of childhood obesity worldwide calls for an intervention earlier in the life cycle. Studies show that nutrition during early infancy may contribute to later obesity. Hence, this study is designed to determine if the variation in complementary feeding practices poses a risk for the development of obesity later in life. A mixed methods approach will be used in conducting this study. Methods and analysis The target participants are infants born from January to June 2015 in the South East Asia Community Observatory (SEACO) platform. The SEACO is a Health and Demographic Surveillance System (HDSS) that is established in the District of Segamat in the state of Johor, Malaysia. For the quantitative strand, the sociodemographic data, feeding practices, anthropometry measurement and total nutrient intake will be assessed. The assessment will occur around the time complementary feeding is expected to start (7 Months) and again at 12 months. A 24-hour diet recall and a 2-day food diary will be used to assess the food intake. For the qualitative strand, selected mothers will be interviewed to explore their infant feeding practices and factors that influence their practices and food choices in detail. Ethics and dissemination Ethical clearance for this study was sought through the Monash University Human Research and Ethics Committee (application number CF14/3850-2014002010). Subsequently, the findings of this study will be disseminated through peer-reviewed journals, national and international conferences.https://doi.org/10.1136/bmjopen-2016-0116356pubpub1

Prevalence of hepatitis B virus infection among blood donors at the Tamale Teaching Hospital, Ghana (2009)

Background: Despite education and availability of drugs and vaccines, hepatitis B virus (HBV) is still the most common severe liver infection in the world accounting for >1 million annual deaths worldwide. Transfusion of infected blood, unprotected sex and mother to child transmission are 3 key transmission routes of HBV in Ghana. There is high incidence of blood demanding health situations in northern Ghana resulting from anemia, accidents, malnutrition, etc. The higher the demand, the higher the possibility of transmitting HBV through infected blood. The aim of the investigation was to estimate the prevalence of HBV in blood donors which will provide justification for interventions that will help minimize or eliminate HBV infection in Ghana. Findings. We investigated the prevalence of HBV infection among blood donors at Tamale Teaching Hospital. The Wondfo HBsAg test kit was used to determine the concentration of HBsAg in 6,462 (576 voluntary and 5,878 replacement) donors as being 1 ng/ml. 10.79% of voluntary donors and 11.59% of replacement donors were HBsAg+. The 20-29 year group of voluntary donors was >2 times more likely to be HBsAg + than 40-60. Also the 20-29 year category of replacement donors was >4 times as likely to be HBsAg + than 50-69. Conclusions: Risk of infection was age, sex and donor type dependent. The 20-29 year category had the highest prevalence of HBsAg + cases, mostly males residing within the metropolis. © 2012 Dongdem et al; licensee BioMed Central Ltd

The rural bite in population pyramids: what are the implications for responsiveness of health systems in middle income countries?

BackgroundHealth services can only be responsive if they are designed to service the needs of the population at hand. In many low and middle income countries, the rate of urbanisation can leave the profile of the rural population quite different from the urban population. As a consequence, the kinds of services required for an urban population may be quite different from that required for a rural population. This is examined using data from the South East Asia Community Observatory in rural Malaysia and contrasting it with the national Malaysia population profile.MethodsCensus data were collected from 10,373 household and the sex and age of household members was recorded. Approximate Malaysian national age and sex profiles were downloaded from the US Census Bureau. The population pyramids, and the dependency and support ratios for the whole population and the SEACO sub-district population are compared.ResultsBased on the population profiles and the dependency ratios, the rural sub-district shows need for health services in the under 14 age group similar to that required nationally. In the older age group, however, the rural sub-district shows twice the need for services as the national data indicate.ConclusionThe health services needs of an older population will tend towards chronic conditions, rather than the typically acute conditions of childhood. The relatively greater number of older people in the rural population suggest a very different health services mix need. Community based population monitoring provides critical information to inform health systems

Complementary feeding and the early origins of obesity risk:A study protocol

Introduction The rise in the prevalence of childhood obesity worldwide calls for an intervention earlier in the life cycle. Studies show that nutrition during early infancy may contribute to later obesity. Hence, this study is designed to determine if the variation in complementary feeding practices poses a risk for the development of obesity later in life. A mixed methods approach will be used in conducting this study.Methods and analysis The target participants are infants born from January to June 2015 in the South East Asia Community Observatory (SEACO) platform. The SEACO is a Health and Demographic Surveillance System (HDSS) that is established in the District of Segamat in the state of Johor, Malaysia. For the quantitative strand, the sociodemographic data, feeding practices, anthropometry measurement and total nutrient intake will be assessed. The assessment will occur around the time complementary feeding is expected to start (7 Months) and again at 12 months. A 24-hour diet recall and a 2-day food diary will be used to assess the food intake. For the qualitative strand, selected mothers will be interviewed to explore their infant feeding practices and factors that influence their practices and food choices in detail.Ethics and dissemination Ethical clearance for this study was sought through the Monash University Human Research and Ethics Committee (application number CF14/3850-2014002010). Subsequently, the findings of this study will be disseminated through peer-reviewed journals, national and international conferences

The rural bite in population pyramids: what are the implications for responsiveness of health systems in middle income countries?

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-0420Background Health services can only be responsive if they are designed to service the needs of the population at hand. In many low and middle income countries, the rate of urbanisation can leave the profile of the rural population quite different from the urban population. As a consequence, the kinds of services required for an urban population may be quite different from that required for a rural population. This is examined using data from the South East Asia Community Observatory in rural Malaysia and contrasting it with the national Malaysia population profile. Methods Census data were collected from 10,373 household and the sex and age of household members was recorded. Approximate Malaysian national age and sex profiles were downloaded from the US Census Bureau. The population pyramids, and the dependency and support ratios for the whole population and the SEACO sub-district population are compared. Results Based on the population profiles and the dependency ratios, the rural sub-district shows need for health services in the under 14 age group similar to that required nationally. In the older age group, however, the rural sub-district shows twice the need for services as the national data indicate. Conclusion The health services needs of an older population will tend towards chronic conditions, rather than the typically acute conditions of childhood. The relatively greater number of older people in the rural population suggest a very different health services mix need. Community based population monitoring provides critical information to inform health systems.https://doi.org/10.1186/1471-2458-14-S2-S814S